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Active inference : the free energy principle in mind, brain, and behavior / / Thomas Parr, Giovanni Pezzulo, and Karl J. Friston
| Active inference : the free energy principle in mind, brain, and behavior / / Thomas Parr, Giovanni Pezzulo, and Karl J. Friston |
| Autore | Parr Thomas <1993-> |
| Pubbl/distr/stampa | Cambridge, Massachusetts : , : The MIT Press, , [2022] |
| Descrizione fisica | 1 online resource (238 pages) |
| Disciplina | 153 |
| Collana | The MIT Press |
| Soggetto topico |
Perception
Inference Neurobiology Human behavior models Knowledge, Theory of Bayesian statistical decision theory |
| Soggetto non controllato |
SCIENCE / Life Sciences / Neuroscience
PSYCHOLOGY / Cognitive Neuroscience & Cognitive Neuropsychology PHILOSOPHY / Mind & Body |
| ISBN |
0-262-36228-7
0-262-36997-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The low road to active inference -- The high road to active inference -- The generative models of active inference -- Message passing and neurobiology -- A recipe for designing active inference models -- Active inference in discrete time -- Active inference in continuous time -- Model based data analysis -- Active inference as a unified theory of sentient behaviour. |
| Record Nr. | UNINA-9910576889803321 |
Parr Thomas <1993->
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| Cambridge, Massachusetts : , : The MIT Press, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Adaptive statistical procedures and related topics : proceedings of a symposium in honor of Herbert Robbins, June 7-11, 1985, Brookhaven National Laboratory, Upton, New York / / edited by John Van Ryzin [[electronic resource]]
| Adaptive statistical procedures and related topics : proceedings of a symposium in honor of Herbert Robbins, June 7-11, 1985, Brookhaven National Laboratory, Upton, New York / / edited by John Van Ryzin [[electronic resource]] |
| Pubbl/distr/stampa | Hayward, Calif., : Institute of Mathematical Statistics, c1986 |
| Descrizione fisica | 1 online resource (ix, 476 p. ) |
| Disciplina | 519.5 |
| Altri autori (Persone) |
RobbinsHerbert
Van RyzinJohn |
| Collana |
Lecture notes-monograph series Adaptive statistical procedures and related topics
Lecture notes-monograph series |
| Soggetto topico |
Sequential analysis
Bayesian statistical decision theory Stochastic approximation Mathematical statistics Probabilities Sequential analysis - Congresses Bayesian statistical decision theory - Congresses Stochastic approximation - Congresses Mathematical statistics - Congresses Probabilities - Congresses Mathematics Physical Sciences & Mathematics Mathematical Statistics |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910482880603321 |
| Hayward, Calif., : Institute of Mathematical Statistics, c1986 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Adaptive statistical procedures and related topics : proceedings of a symposium in honor of Herbert Robbins, June 7-11, 1985, Brookhaven National Laboratory, Upton, New York / / edited by John Van Ryzin [[electronic resource]]
| Adaptive statistical procedures and related topics : proceedings of a symposium in honor of Herbert Robbins, June 7-11, 1985, Brookhaven National Laboratory, Upton, New York / / edited by John Van Ryzin [[electronic resource]] |
| Pubbl/distr/stampa | Hayward, Calif., : Institute of Mathematical Statistics, c1986 |
| Descrizione fisica | 1 online resource (ix, 476 p. ) |
| Disciplina | 519.5 |
| Altri autori (Persone) |
RobbinsHerbert
Van RyzinJohn |
| Collana |
Lecture notes-monograph series Adaptive statistical procedures and related topics
Lecture notes-monograph series |
| Soggetto topico |
Sequential analysis
Bayesian statistical decision theory Stochastic approximation Mathematical statistics Probabilities Sequential analysis - Congresses Bayesian statistical decision theory - Congresses Stochastic approximation - Congresses Mathematical statistics - Congresses Probabilities - Congresses Mathematics Physical Sciences & Mathematics Mathematical Statistics |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996210819903316 |
| Hayward, Calif., : Institute of Mathematical Statistics, c1986 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advanced mapping of environmental data [[electronic resource] ] : geostatistics, machine learning, and Bayesian maximum entropy / / edited by Mikhail Kanevski
| Advanced mapping of environmental data [[electronic resource] ] : geostatistics, machine learning, and Bayesian maximum entropy / / edited by Mikhail Kanevski |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (xiii, 313 p.) : ill |
| Disciplina | 550.1519542 |
| Altri autori (Persone) | KanevskiMikhail |
| Collana | ISTE |
| Soggetto topico |
Geology - Statistical methods
Machine learning Bayesian statistical decision theory |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9780470611463 (e-book)
9781848210608 (hbk.) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Advanced Mapping of Environmental Data: Introduction -- Chapter 2. Environmental Monitoring Network Characterization and Clustering -- Chapter 3. Geostatistics: Spatial Predictions and Simulations -- Chapter 4. Spatial Data Analysis and Mapping Using Machine Learning Algorithms -- Chapter 5. Advanced Mapping of Environmental Spatial Data: Case Studies -- Chapter 6. Bayesian Maximum Entropy – BME -- Index. |
| Record Nr. | UNINA-9910139505003321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advanced mapping of environmental data [[electronic resource] ] : geostatistics, machine learning, and Bayesian maximum entropy / / edited by Mikhail Kanevski
| Advanced mapping of environmental data [[electronic resource] ] : geostatistics, machine learning, and Bayesian maximum entropy / / edited by Mikhail Kanevski |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (xiii, 313 p.) : ill |
| Disciplina | 550.1519542 |
| Altri autori (Persone) | KanevskiMikhail |
| Collana | ISTE |
| Soggetto topico |
Geology - Statistical methods
Machine learning Bayesian statistical decision theory |
| ISBN |
9780470611463 (e-book)
9781848210608 (hbk.) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Advanced Mapping of Environmental Data: Introduction -- Chapter 2. Environmental Monitoring Network Characterization and Clustering -- Chapter 3. Geostatistics: Spatial Predictions and Simulations -- Chapter 4. Spatial Data Analysis and Mapping Using Machine Learning Algorithms -- Chapter 5. Advanced Mapping of Environmental Spatial Data: Case Studies -- Chapter 6. Bayesian Maximum Entropy – BME -- Index. |
| Record Nr. | UNINA-9910830444603321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced mapping of environmental data : geostatistics, machine learning, and Bayesian maximum entropy / / edited by Mikhail Kanevski
| Advanced mapping of environmental data : geostatistics, machine learning, and Bayesian maximum entropy / / edited by Mikhail Kanevski |
| Pubbl/distr/stampa | London, : ISTE, Ltd. |
| Descrizione fisica | 1 online resource (xiii, 313 p.) : ill |
| Disciplina | 550.1/519542 |
| Altri autori (Persone) | KanevskiMikhail |
| Collana | ISTE |
| Soggetto topico |
Geology - Statistical methods
Machine learning Bayesian statistical decision theory |
| ISBN |
9780470611463 (e-book)
9781848210608 (hbk.) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Advanced Mapping of Environmental Data: Introduction -- Chapter 2. Environmental Monitoring Network Characterization and Clustering -- Chapter 3. Geostatistics: Spatial Predictions and Simulations -- Chapter 4. Spatial Data Analysis and Mapping Using Machine Learning Algorithms -- Chapter 5. Advanced Mapping of Environmental Spatial Data: Case Studies -- Chapter 6. Bayesian Maximum Entropy – BME -- Index. |
| Record Nr. | UNINA-9910877036303321 |
| London, : ISTE, Ltd. | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler
| Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler |
| Autore | Mahler Ronald P. S. |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2014 |
| Descrizione fisica | 1 online resource (1167 p.) |
| Disciplina | 006.33 |
| Collana | Artech House electronic warfare library |
| Soggetto topico |
Expert systems (Computer science)
Multisensor data fusion - Mathematics Bayesian statistical decision theory |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-60807-799-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface; Acknowledgments; Chapter 1 Introduction to the Book; 1.1 OVERVIEW OF FINITE-SET STATISTICS; 1.2 RECENT ADVANCES IN FINITE-SET STATISTICS; 1.3 ORGANIZATION OF THE BOOK; Part I Elements of Finite-Set Statistics; Chapter 2 Random Finite Sets; 2.1 INTRODUCTION; 2.2 SINGLE-SENSOR, SINGLE-TARGET STATISTICS; 2.3 RANDOM FINITE SETS (RFSs); 2.4 MULTIOBJECT STATISTICS IN A NUTSHELL; Chapter 3 Multiobject Calculus; 3.1 INTRODUCTION; 3.2 BASIC CONCEPTS; 3.3 SET INTEGRALS; 3.4 MULTIOBJECT DIFFERENTIAL CALCULUS; 3.5 KEY FORMULAS OF MULTIOBJECT CALCULUS.
Chapter 4 Multiobject Statistics4.1 INTRODUCTION; 4.2 BASIC MULTIOBJECT STATISTICAL DESCRIPTORS; 4.3 IMPORTANT MULTIOBJECT PROCESSES; 4.4 BASIC DERIVED RFSs; Chapter 5 Multiobject Modeling and Filtering; 5.1 INTRODUCTION; 5.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 5.3 MULTITARGET BAYES OPTIMALITY; 5.4 RFS MULTITARGET MOTION MODELS; 5.5 RFS MULTITARGET MEASUREMENT MODELS; 5.6 MULTITARGET MARKOV DENSITIES; 5.7 MULTISENSOR-MULTITARGET LIKELIHOOD FUNCTIONS; 5.8 THE MULTITARGET BAYES FILTER IN p.g.fl -- FORM; 5.9 THE FACTORED MULTITARGET BAYES FILTER; 5.10 APPROXIMATE MULTITARGET FILTERS. Chapter 6 Multiobject Metrology6.1 INTRODUCTION; 6.2 MULTIOBJECT MISS DISTANCE; 6.3 MULTIOBJECT INFORMATION FUNCTIONALS; Part II RFS Filters: StandardMeasurement Model; Chapter 7 Introduction to Part II; 7.1 SUMMARY OF MAJOR LESSONS LEARNED; 7.2 STANDARD MULTITARGET MEASUREMENT MODEL; 7.3 AN APPROXIMATE STANDARD LIKELIHOOD FUNCTION; 7.4 STANDARD MULTITARGET MOTION MODEL; 7.5 STANDARD MOTION MODEL WITH TARGET SPAWNING; 7.6 ORGANIZATION OF PART II; Chapter 8 Classical PHD and CPHD Filters; 8.1 INTRODUCTION; 8.2 A GENERAL PHD FILTER; 8.3 ARBITRARY-CLUTTER PHD FILTER; 8.4 CLASSICAL PHD FILTER. 8.5 CLASSICAL CARDINALIZED PHD (CPHD) FILTER8.6 ZERO FALSE ALARMS (ZFA) CPHD FILTER; 8.7 PHD FILTER FOR STATE-DEPENDENT POISSON CLUTTER; Chapter 9 Implementing Classical PHD/CPHDFilters; 9.1 INTRODUCTION; 9.2 "SPOOKY ACTION AT A DISTANCE"; 9.3 MERGING AND SPLITTING FOR PHD FILTERS; 9.4 MERGING AND SPLITTING FOR CPHD FILTERS; 9.5 GAUSSIAN MIXTURE (GM) IMPLEMENTATION; 9.6 SEQUENTIAL MONTE CARLO (SMC) IMPLEMENTATION; Chapter 10 Multisensor PHD and CPHD Filters; 10.1 INTRODUCTION; 10.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 10.3 THE GENERAL MULTISENSOR PHD FILTER. 10.4 THE MULTISENSOR CLASSICAL PHD FILTER10.5 ITERATED-CORRECTOR MULTISENSOR PHD/CPHD FILTERS; 10.6 PARALLEL COMBINATION MULTISENSOR PHD AND CPHD FILTERS; 10.7 AN ERRONEOUS "AVERAGED" MULTISENSOR PHD FILTER; 10.8 PERFORMANCE COMPARISONS; Chapter 11 Jump-Markov PHD/CPHD Filters; 11.1 INTRODUCTION; 11.2 JUMP-MARKOV FILTERS: A REVIEW; 11.3 MULTITARGET JUMP-MARKOV SYSTEMS; 11.4 JUMP-MARKOV PHD FILTER; 11.5 JUMP-MARKOV CPHD FILTER; 11.6 VARIABLE STATE SPACE JUMP-MARKOV CPHD FILTERS; 11.7 IMPLEMENTING JUMP-MARKOV PHD/CPHD FILTERS; 11.8 IMPLEMENTED JUMP-MARKOV PHD/CPHD FILTERS. |
| Record Nr. | UNINA-9910460377903321 |
|
Mahler Ronald P. S.
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||
| Boston : , : Artech House, , ©2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler
| Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler |
| Autore | Mahler Ronald P. S. |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2014 |
| Descrizione fisica | 1 online resource (1167 p.) |
| Disciplina | 006.33 |
| Collana | Artech House electronic warfare library |
| Soggetto topico |
Expert systems (Computer science)
Multisensor data fusion - Mathematics Bayesian statistical decision theory |
| ISBN | 1-60807-799-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface; Acknowledgments; Chapter 1 Introduction to the Book; 1.1 OVERVIEW OF FINITE-SET STATISTICS; 1.2 RECENT ADVANCES IN FINITE-SET STATISTICS; 1.3 ORGANIZATION OF THE BOOK; Part I Elements of Finite-Set Statistics; Chapter 2 Random Finite Sets; 2.1 INTRODUCTION; 2.2 SINGLE-SENSOR, SINGLE-TARGET STATISTICS; 2.3 RANDOM FINITE SETS (RFSs); 2.4 MULTIOBJECT STATISTICS IN A NUTSHELL; Chapter 3 Multiobject Calculus; 3.1 INTRODUCTION; 3.2 BASIC CONCEPTS; 3.3 SET INTEGRALS; 3.4 MULTIOBJECT DIFFERENTIAL CALCULUS; 3.5 KEY FORMULAS OF MULTIOBJECT CALCULUS.
Chapter 4 Multiobject Statistics4.1 INTRODUCTION; 4.2 BASIC MULTIOBJECT STATISTICAL DESCRIPTORS; 4.3 IMPORTANT MULTIOBJECT PROCESSES; 4.4 BASIC DERIVED RFSs; Chapter 5 Multiobject Modeling and Filtering; 5.1 INTRODUCTION; 5.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 5.3 MULTITARGET BAYES OPTIMALITY; 5.4 RFS MULTITARGET MOTION MODELS; 5.5 RFS MULTITARGET MEASUREMENT MODELS; 5.6 MULTITARGET MARKOV DENSITIES; 5.7 MULTISENSOR-MULTITARGET LIKELIHOOD FUNCTIONS; 5.8 THE MULTITARGET BAYES FILTER IN p.g.fl -- FORM; 5.9 THE FACTORED MULTITARGET BAYES FILTER; 5.10 APPROXIMATE MULTITARGET FILTERS. Chapter 6 Multiobject Metrology6.1 INTRODUCTION; 6.2 MULTIOBJECT MISS DISTANCE; 6.3 MULTIOBJECT INFORMATION FUNCTIONALS; Part II RFS Filters: StandardMeasurement Model; Chapter 7 Introduction to Part II; 7.1 SUMMARY OF MAJOR LESSONS LEARNED; 7.2 STANDARD MULTITARGET MEASUREMENT MODEL; 7.3 AN APPROXIMATE STANDARD LIKELIHOOD FUNCTION; 7.4 STANDARD MULTITARGET MOTION MODEL; 7.5 STANDARD MOTION MODEL WITH TARGET SPAWNING; 7.6 ORGANIZATION OF PART II; Chapter 8 Classical PHD and CPHD Filters; 8.1 INTRODUCTION; 8.2 A GENERAL PHD FILTER; 8.3 ARBITRARY-CLUTTER PHD FILTER; 8.4 CLASSICAL PHD FILTER. 8.5 CLASSICAL CARDINALIZED PHD (CPHD) FILTER8.6 ZERO FALSE ALARMS (ZFA) CPHD FILTER; 8.7 PHD FILTER FOR STATE-DEPENDENT POISSON CLUTTER; Chapter 9 Implementing Classical PHD/CPHDFilters; 9.1 INTRODUCTION; 9.2 "SPOOKY ACTION AT A DISTANCE"; 9.3 MERGING AND SPLITTING FOR PHD FILTERS; 9.4 MERGING AND SPLITTING FOR CPHD FILTERS; 9.5 GAUSSIAN MIXTURE (GM) IMPLEMENTATION; 9.6 SEQUENTIAL MONTE CARLO (SMC) IMPLEMENTATION; Chapter 10 Multisensor PHD and CPHD Filters; 10.1 INTRODUCTION; 10.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 10.3 THE GENERAL MULTISENSOR PHD FILTER. 10.4 THE MULTISENSOR CLASSICAL PHD FILTER10.5 ITERATED-CORRECTOR MULTISENSOR PHD/CPHD FILTERS; 10.6 PARALLEL COMBINATION MULTISENSOR PHD AND CPHD FILTERS; 10.7 AN ERRONEOUS "AVERAGED" MULTISENSOR PHD FILTER; 10.8 PERFORMANCE COMPARISONS; Chapter 11 Jump-Markov PHD/CPHD Filters; 11.1 INTRODUCTION; 11.2 JUMP-MARKOV FILTERS: A REVIEW; 11.3 MULTITARGET JUMP-MARKOV SYSTEMS; 11.4 JUMP-MARKOV PHD FILTER; 11.5 JUMP-MARKOV CPHD FILTER; 11.6 VARIABLE STATE SPACE JUMP-MARKOV CPHD FILTERS; 11.7 IMPLEMENTING JUMP-MARKOV PHD/CPHD FILTERS; 11.8 IMPLEMENTED JUMP-MARKOV PHD/CPHD FILTERS. |
| Record Nr. | UNINA-9910797934303321 |
|
Mahler Ronald P. S.
|
||
| Boston : , : Artech House, , ©2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler
| Advances in statistical multisource-multitarget information fusion / / Ronald P.S. Mahler |
| Autore | Mahler Ronald P. S. |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2014 |
| Descrizione fisica | 1 online resource (1167 p.) |
| Disciplina | 006.33 |
| Collana | Artech House electronic warfare library |
| Soggetto topico |
Expert systems (Computer science)
Multisensor data fusion - Mathematics Bayesian statistical decision theory |
| ISBN | 1-60807-799-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface; Acknowledgments; Chapter 1 Introduction to the Book; 1.1 OVERVIEW OF FINITE-SET STATISTICS; 1.2 RECENT ADVANCES IN FINITE-SET STATISTICS; 1.3 ORGANIZATION OF THE BOOK; Part I Elements of Finite-Set Statistics; Chapter 2 Random Finite Sets; 2.1 INTRODUCTION; 2.2 SINGLE-SENSOR, SINGLE-TARGET STATISTICS; 2.3 RANDOM FINITE SETS (RFSs); 2.4 MULTIOBJECT STATISTICS IN A NUTSHELL; Chapter 3 Multiobject Calculus; 3.1 INTRODUCTION; 3.2 BASIC CONCEPTS; 3.3 SET INTEGRALS; 3.4 MULTIOBJECT DIFFERENTIAL CALCULUS; 3.5 KEY FORMULAS OF MULTIOBJECT CALCULUS.
Chapter 4 Multiobject Statistics4.1 INTRODUCTION; 4.2 BASIC MULTIOBJECT STATISTICAL DESCRIPTORS; 4.3 IMPORTANT MULTIOBJECT PROCESSES; 4.4 BASIC DERIVED RFSs; Chapter 5 Multiobject Modeling and Filtering; 5.1 INTRODUCTION; 5.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 5.3 MULTITARGET BAYES OPTIMALITY; 5.4 RFS MULTITARGET MOTION MODELS; 5.5 RFS MULTITARGET MEASUREMENT MODELS; 5.6 MULTITARGET MARKOV DENSITIES; 5.7 MULTISENSOR-MULTITARGET LIKELIHOOD FUNCTIONS; 5.8 THE MULTITARGET BAYES FILTER IN p.g.fl -- FORM; 5.9 THE FACTORED MULTITARGET BAYES FILTER; 5.10 APPROXIMATE MULTITARGET FILTERS. Chapter 6 Multiobject Metrology6.1 INTRODUCTION; 6.2 MULTIOBJECT MISS DISTANCE; 6.3 MULTIOBJECT INFORMATION FUNCTIONALS; Part II RFS Filters: StandardMeasurement Model; Chapter 7 Introduction to Part II; 7.1 SUMMARY OF MAJOR LESSONS LEARNED; 7.2 STANDARD MULTITARGET MEASUREMENT MODEL; 7.3 AN APPROXIMATE STANDARD LIKELIHOOD FUNCTION; 7.4 STANDARD MULTITARGET MOTION MODEL; 7.5 STANDARD MOTION MODEL WITH TARGET SPAWNING; 7.6 ORGANIZATION OF PART II; Chapter 8 Classical PHD and CPHD Filters; 8.1 INTRODUCTION; 8.2 A GENERAL PHD FILTER; 8.3 ARBITRARY-CLUTTER PHD FILTER; 8.4 CLASSICAL PHD FILTER. 8.5 CLASSICAL CARDINALIZED PHD (CPHD) FILTER8.6 ZERO FALSE ALARMS (ZFA) CPHD FILTER; 8.7 PHD FILTER FOR STATE-DEPENDENT POISSON CLUTTER; Chapter 9 Implementing Classical PHD/CPHDFilters; 9.1 INTRODUCTION; 9.2 "SPOOKY ACTION AT A DISTANCE"; 9.3 MERGING AND SPLITTING FOR PHD FILTERS; 9.4 MERGING AND SPLITTING FOR CPHD FILTERS; 9.5 GAUSSIAN MIXTURE (GM) IMPLEMENTATION; 9.6 SEQUENTIAL MONTE CARLO (SMC) IMPLEMENTATION; Chapter 10 Multisensor PHD and CPHD Filters; 10.1 INTRODUCTION; 10.2 THE MULTISENSOR-MULTITARGET BAYES FILTER; 10.3 THE GENERAL MULTISENSOR PHD FILTER. 10.4 THE MULTISENSOR CLASSICAL PHD FILTER10.5 ITERATED-CORRECTOR MULTISENSOR PHD/CPHD FILTERS; 10.6 PARALLEL COMBINATION MULTISENSOR PHD AND CPHD FILTERS; 10.7 AN ERRONEOUS "AVERAGED" MULTISENSOR PHD FILTER; 10.8 PERFORMANCE COMPARISONS; Chapter 11 Jump-Markov PHD/CPHD Filters; 11.1 INTRODUCTION; 11.2 JUMP-MARKOV FILTERS: A REVIEW; 11.3 MULTITARGET JUMP-MARKOV SYSTEMS; 11.4 JUMP-MARKOV PHD FILTER; 11.5 JUMP-MARKOV CPHD FILTER; 11.6 VARIABLE STATE SPACE JUMP-MARKOV CPHD FILTERS; 11.7 IMPLEMENTING JUMP-MARKOV PHD/CPHD FILTERS; 11.8 IMPLEMENTED JUMP-MARKOV PHD/CPHD FILTERS. |
| Record Nr. | UNINA-9910816058003321 |
|
Mahler Ronald P. S.
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||
| Boston : , : Artech House, , ©2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The anatomy of bias [[electronic resource] ] : how neural circuits weigh the options / / Jan Lauwereyns
| The anatomy of bias [[electronic resource] ] : how neural circuits weigh the options / / Jan Lauwereyns |
| Autore | Lauwereyns Jan <1969-> |
| Pubbl/distr/stampa | Cambridge, MA, : MIT Press, c2010 |
| Descrizione fisica | 1 online resource (xviii, 262 p.) : ill |
| Disciplina | 153.8/3 |
| Soggetto topico |
Neural circuitry - Mathematical models
Decision making - Physiological aspects Bayesian statistical decision theory Neural networks (Neurobiology) - Mathematical models |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-282-54193-5
9786612541933 0-262-27799-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910455605703321 |
|
Lauwereyns Jan <1969->
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| Cambridge, MA, : MIT Press, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Soggetto topico
-
Bayesian statistical decision theory
(304)
- Mathematical statistics (25)
- Econometrics (14)
- Statistical decision (14)
- Probabilities (13)